Assessing the performance of American chief complaint classifiers on Victorian syndromic surveillance data

Syndromic surveillance systems aim to support early detection of salient disease outbreaks, and to shed timely light on the size and spread of pandemic outbreaks. They can also be used more generally to monitor disease trends and provide reassurance that an outbreak has not occurred. One commonly used technique for syndromic surveillance is concerned with classifying Emergency Department data, such as chief complaints or triage notes, into a set of pre-defined syndromic groups. This paper reports our findings on the investigation of the utility and effectiveness of two existing North American methods for free-text chief complaint classification on a large data set of Australian Emergency Department triage notes, collected from two hospitals in the state of Victoria. To our knowledge, these methods have never before been analysed and compared against each other for their applicability and effectiveness on free text chief complaint classification at this scale or in the Australian context.